Wireless sensors and IoT platform for intelligent HVAC control

Detalhes bibliográficos
Autor(a) principal: Ruano, Antonio
Data de Publicação: 2018
Outros Autores: Silva, Sergio, Duarte, Hélder, Ferreira, Pedro M.
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10400.1/11602
Resumo: Energy consumption of buildings (residential and non-residential) represents approximately 40% of total world electricity consumption, with half of this energy consumed by HVAC systems. Model-Based Predictive Control (MBPC) is perhaps the technique most often proposed for HVAC control, since it offers an enormous potential for energy savings. Despite the large number of papers on this topic during the last few years, there are only a few reported applications of the use of MBPC for existing buildings, under normal occupancy conditions and, to the best of our knowledge, no commercial solution yet. A marketable solution has been recently presented by the authors, coined the IMBPC HVAC system. This paper describes the design, prototyping and validation of two components of this integrated system, the Self-Powered Wireless Sensors and the IOT platform developed. Results for the use of IMBPC in a real building under normal occupation demonstrate savings in the electricity bill while maintaining thermal comfort during the whole occupation schedule.
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spelling Wireless sensors and IoT platform for intelligent HVAC controlPredictive ControlThermal ComfortNeural-NetworksBuildingsSystemModelsEnergy consumption of buildings (residential and non-residential) represents approximately 40% of total world electricity consumption, with half of this energy consumed by HVAC systems. Model-Based Predictive Control (MBPC) is perhaps the technique most often proposed for HVAC control, since it offers an enormous potential for energy savings. Despite the large number of papers on this topic during the last few years, there are only a few reported applications of the use of MBPC for existing buildings, under normal occupancy conditions and, to the best of our knowledge, no commercial solution yet. A marketable solution has been recently presented by the authors, coined the IMBPC HVAC system. This paper describes the design, prototyping and validation of two components of this integrated system, the Self-Powered Wireless Sensors and the IOT platform developed. Results for the use of IMBPC in a real building under normal occupation demonstrate savings in the electricity bill while maintaining thermal comfort during the whole occupation schedule.QREN SIDT [38798]; Portuguese Foundation for Science & Technology, through IDMEC, under LAETA [ID/EMS/50022/2013]MDPISapientiaRuano, AntonioSilva, SergioDuarte, HélderFerreira, Pedro M.2018-12-07T14:53:37Z2018-032018-03-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10400.1/11602eng2076-341710.3390/app8030370info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-07-24T10:23:26Zoai:sapientia.ualg.pt:10400.1/11602Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T20:03:05.200654Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv Wireless sensors and IoT platform for intelligent HVAC control
title Wireless sensors and IoT platform for intelligent HVAC control
spellingShingle Wireless sensors and IoT platform for intelligent HVAC control
Ruano, Antonio
Predictive Control
Thermal Comfort
Neural-Networks
Buildings
System
Models
title_short Wireless sensors and IoT platform for intelligent HVAC control
title_full Wireless sensors and IoT platform for intelligent HVAC control
title_fullStr Wireless sensors and IoT platform for intelligent HVAC control
title_full_unstemmed Wireless sensors and IoT platform for intelligent HVAC control
title_sort Wireless sensors and IoT platform for intelligent HVAC control
author Ruano, Antonio
author_facet Ruano, Antonio
Silva, Sergio
Duarte, Hélder
Ferreira, Pedro M.
author_role author
author2 Silva, Sergio
Duarte, Hélder
Ferreira, Pedro M.
author2_role author
author
author
dc.contributor.none.fl_str_mv Sapientia
dc.contributor.author.fl_str_mv Ruano, Antonio
Silva, Sergio
Duarte, Hélder
Ferreira, Pedro M.
dc.subject.por.fl_str_mv Predictive Control
Thermal Comfort
Neural-Networks
Buildings
System
Models
topic Predictive Control
Thermal Comfort
Neural-Networks
Buildings
System
Models
description Energy consumption of buildings (residential and non-residential) represents approximately 40% of total world electricity consumption, with half of this energy consumed by HVAC systems. Model-Based Predictive Control (MBPC) is perhaps the technique most often proposed for HVAC control, since it offers an enormous potential for energy savings. Despite the large number of papers on this topic during the last few years, there are only a few reported applications of the use of MBPC for existing buildings, under normal occupancy conditions and, to the best of our knowledge, no commercial solution yet. A marketable solution has been recently presented by the authors, coined the IMBPC HVAC system. This paper describes the design, prototyping and validation of two components of this integrated system, the Self-Powered Wireless Sensors and the IOT platform developed. Results for the use of IMBPC in a real building under normal occupation demonstrate savings in the electricity bill while maintaining thermal comfort during the whole occupation schedule.
publishDate 2018
dc.date.none.fl_str_mv 2018-12-07T14:53:37Z
2018-03
2018-03-01T00:00:00Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10400.1/11602
url http://hdl.handle.net/10400.1/11602
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 2076-3417
10.3390/app8030370
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
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dc.publisher.none.fl_str_mv MDPI
publisher.none.fl_str_mv MDPI
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instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron:RCAAP
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instacron_str RCAAP
institution RCAAP
reponame_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
collection Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
repository.name.fl_str_mv Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
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